fMRI is a powerful tool used in the study of brain function. It can noninvasively detect signal changes in areas of the brain where neuronal activity is varying. This chapter is a comprehensive description of the various steps in the statistical analysis of fMRI data. This will cover topics such as the general linear model (including orthogonality, hemodynamic variability, noise modeling, and the use of contrasts), multisubject statistics, and statistical thresholding (including random field theory and permutation methods).
CITATION STYLE
Woolrich, M. W., Beckmann, C. F., Nichols, T. E., & Smith, S. M. (2016). Statistical analysis of fMRI data. In Neuromethods (Vol. 119, pp. 183–239). Humana Press Inc. https://doi.org/10.1007/978-1-4939-5611-1_7
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